DNA copy number detection from exome sequencing - Exploiting the off-targets
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Oscar Krijgsman
PROVIDER: E-GEOD-60259 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. DNA copy number profiles generated with a new tool, ENCODER, were compared to DNA copy number profiles from SNP6, NimbleGen and low-coverage Whole Genome Sequencing. DNA copy number profiles of mouse squamous cell lung cancer (SCLC) were generated with ENCODER from whole exome sequencing data and compared to results from the NimbleGen array
2014-08-12 | E-GEOD-60254 | biostudies-arrayexpress
Project description:Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. DNA copy number profiles generated with a new tool, ENCODER, were compared to DNA copy number profiles from SNP6, NimbleGen and low-coverage Whole Genome Sequencing. DNA copy number profiles of melanoma PDX sample were generated with ENCODER from whole exome sequencing data and compared to results from the SNP6 platform.
2014-08-12 | E-GEOD-60168 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the SubSeries listed below.
2014-08-12 | GSE60259 | GEO
Project description:The EBF1-PDGFRB gene fusion accounts for <1% B-cell precursor acute lymphoblastic leukaemia and occurs within the Philadelphia-like ALL subtype. We performed Affymetrix SNP 6.0 array was undertaken patients who tested positive for EBF1-PDGFRB rearrangement by FISH and/or RT-PCR. We performed Affymetrix SNP 6.0 array on genomic DNA extracted from bone marrow samples taken at diagnosis in 9 patients, at relapse in one patient and at remission in one patient.
2016-04-05 | E-GEOD-77557 | biostudies-arrayexpress
Project description:One aspect of intra-tumoral heterogeneity in glioblastoma involves subpopulations of cells capable of self-renewal and indefinite propagation. Conceptually, this capacity is frequently treated as a static property. Here we provide data suggesting that tumorigenicity in glioblastomais a dynamic property that can be acquired or lost. Integrated expression analyses suggest that tumorigenicity is determined by the level of MYC expression relative to a threshold. Transitions between tumorigenic and non-tumorigenic cell states are associated with changes in histone modifications at the MYC locus, suggesting tumorigenicity is epigenetically regulated. To verify genomic stability at the nucleotide level, we tested whether subclones derived from single cells shared common Single-Nucleotide Polymorphisms (SNPs). Ten single cell-derived subclones of U87MG underwent SNP profiling by Affymetrix Human Mapping 250K Nsp arrays.
2014-03-28 | E-GEOD-56316 | biostudies-arrayexpress
Project description:Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. DNA copy number profiles generated with a new tool, ENCODER, were compared to DNA copy number profiles from SNP6, NimbleGen and low-coverage Whole Genome Sequencing.
2014-08-12 | GSE60168 | GEO
Project description:Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. DNA copy number profiles generated with a new tool, ENCODER, were compared to DNA copy number profiles from SNP6, NimbleGen and low-coverage Whole Genome Sequencing.
2014-08-12 | GSE60254 | GEO
Project description:Introduction: Cis-acting regulatory single nucleotide polymorphisms (SNPs) at specific loci may modulate penetrance of germline mutations at the same loci by introducing different levels of expression of the wild-type allele. We have previously reported that BRCA2 shows differential allelic expression and we hypothesize that the known variable penetrance of BRCA2 mutations might be associated with this mechanism. Methods: We combined haplotype analysis and differential allelic expression of BRCA2 in breast tissue to identify expression haplotypes and candidate cis-regulatory variants. These candidate variants underwent selection based on in-silico predictions for regulatory potential and disruption of transcription factor binding, and were functionally analysed in-vitro and in-vivo in normal and breast cancer cell lines. SNPs tagging the expression haplotypes were correlated with the total expression of several genes in breast tissue measured by Taqman and microarray technologies. The effect of the expression haplotypes on breast cancer risk in BRCA2 mutation carriers was investigated in 2754 carriers. Results: We identified common haplotypes associated with differences in the levels of BRCA2 expression in human breast cells. We characterised three cis-regulatory SNPs located at the promoter and two intronic regulatory elements, which affect the binding of the transcription factors C/EBPα, HMGA1, DBP and ZF5. We showed that the expression haplotypes also correlated with changes in the expression of other genes in normal breast. Furthermore, there was suggestive evidence that the minor allele of SNP rs4942440, which is associated with higher BRCA2 expression, is also associated with a reduced risk of breast cancer (per-allele HR=0.85, 95%CI=0.72-1.00, P-trend=0.048). Conclusion: Our work provides further insights into the role of cis-regulatory variation in the penetrance of disease-causing mutations. We identified small-effect genetic variants associated with allelic expression differences in BRCA2, which could possibly affect the risk in mutation carriers through altering expression levels of the wild-type allele. Genotype of normal breast sample from healthy controls.
2012-02-01 | E-GEOD-32258 | biostudies-arrayexpress
Project description:Copy number profile of cultured Breast Cancer cell line measured by Affymetrix SNPs microarrays Whole genome copy number profile of 2 breast cancer cell lines were analyzed using Affymetrix SNP6.0 arrays
2015-08-07 | E-GEOD-66070 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the following subset Series: GSE30274: The histotype-specific copy-number landscape of ovarian cancer (expression Japan) GSE30283: The histotype-specific copy-number landscape of ovarian cancer (copy number Japan) GSE30284: The histotype-specific copy-number landscape of ovarian cancer (expression Taiwan) GSE30300: The histotype-specific copy-number landscape of ovarian cancer (copy number SNP) Refer to individual Series
2012-10-25 | E-GEOD-30311 | biostudies-arrayexpress